Evidence map›Paper›PMID 31263100›Full record

ArticleScientific data2019

A dataset of distribution and diversity of ticks in China.

Guanshi Zhang, Duo Zheng, Yuqin Tian, Sen Li

Abstract readDataset
In one paragraph

Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Distribution ofInternational journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Guanshi ZhangSchool of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, P.R. China.
Duo ZhengSchool of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, P.R. China.
Yuqin TianSchool of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, P.R. China.
Sen LiSchool of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, P.R. China. senli@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While tick-borne zoonoses, such as Lyme disease and tick-borne encephalitis, present an increasing global concern, knowledge of their vectors' distribution remains limited, especially for China. In this paper, we present the first comprehensive dataset of known tick species and their distributions in China, derived from peer-reviewed literature published between 1960 and 2017. We searched for journal articles, conference papers and degree thesis published in both English and Chinese, extracted geographic information associated with tick occurrence, and applied quality-control procedures to remove duplicates and ensure accuracy. The dataset contains 5731 records of geo-referenced occurrences for 123 tick species distributed over 1141 locations distinguished at four levels of scale i.e., provincial, prefectural, county, and township and finer. The most frequently reported tick species include Haemaphysalis longicornis, Dermacentor silvarum, Ixodes persulcatus, Haemaphysalis conicinna, Rhipicephalus microplus, and Rhipicephalus sanguineus sensu lato. The geographical dataset provides an improved map of where ticks inhabit China and can be used for a variety of spatial analyses of ticks and the risk of zoonoses they transmit.

Indexed as

TicksAnimalsChinaInsect VectorsMolecular Epidemiology

Identifiers

PMID31263100
PMCPMC6602924

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.